Vision-based system for acquiring crop residue data and related calibration methods

ABSTRACT

A method for calibrating crop residue data for a field acquired using a vision-based system may include receiving image data associated with an imaged portion of the field, analyzing the image data using a first residue-estimating technique to determine a first estimated value of a crop residue parameter for the imaged portion of the field, and analyzing the image data using a second residue-estimating technique to determine a second estimated value of the crop residue parameter for the imaged portion of the field. In addition, when a differential exists between the first and second estimated values, the method may also include adjusting at least one of the first estimated value or one or more additional estimated values of the crop residue parameter determined using the first residue-estimating technique based on at least one of the second estimated value or the differential between first and second estimated values.

FIELD OF THE INVENTION

The present subject matter relates generally to a vision-based systemfor automatically acquiring crop residue data while an operation (e.g.,a tillage operation) is being performed within a field and, moreparticularly, to related methods for calibrating a vision-based systemused to acquire crop residue data.

BACKGROUND OF THE INVENTION

Crop residue generally refers to the vegetation (e.g., straw, chaff,husks, cobs) remaining on the soil surface following the performance ofa given agricultural operation, such as a harvesting operation or atillage operation. For various reasons, it is important to maintain agiven amount of crop residue within a field following an agriculturaloperation. Specifically, crop residue remaining within the field canhelp in maintaining the content of organic matter within the soil andcan also serve to protect the soil from wind and water erosion. However,in some cases, leaving an excessive amount of crop residue within afield can have a negative effect on the soil's productivity potential,such as by slowing down the warming of the soil at planting time and/orby slowing down seed germination. As such, the ability to monitor and/oradjust the amount of crop residue remaining within a field can be veryimportant to maintaining a healthy, productive field, particularly whenit comes to performing tillage operations.

In this regard, vision-based systems have been developed that attempt toestimate crop residue coverage from images captured of the field.However, such vision-based systems suffer from various drawbacks ordisadvantages, particularly with reference to the accuracy of the cropresidue estimates provided through the use of computer-aided imageprocessing techniques.

Accordingly, an improved vision-based system for acquiring crop residuedata and related methods for calibrating such a system to improve theaccuracy of the crop residue estimates provided therewith would bewelcomed in the technology.

BRIEF DESCRIPTION OF THE INVENTION

Aspects and advantages of the invention will be set forth in part in thefollowing description, or may be obvious from the description, or may belearned through practice of the invention.

In one aspect, the present subject matter is directed to a method forcalibrating crop residue data for a field acquired using a vision-basedsystem. The method may include controlling, with a computing device, anoperation of at least one of an implement or a work vehicle as theimplement is being towed by the work vehicle across the field andreceiving, with the computing device, image data associated with animaged portion of the field. In addition, the method may includeanalyzing, with the computing device, the image data using a firstresidue-estimating technique to determine a first estimated value of acrop residue parameter for the imaged portion of the field andanalyzing, with the computing device, the image data using a secondresidue-estimating technique to determine a second estimated value ofthe crop residue parameter for the imaged portion of the field, whereinthe second residue-estimating technique differs from the firstresidue-estimating technique. Moreover, when a differential existsbetween the first and second estimated values, the method may alsoinclude adjusting at least one of the first estimated value or one ormore additional estimated values of the crop residue parameterdetermined using the first residue-estimating technique based on atleast one of the second estimated value or the differential betweenfirst and second estimated values.

In another aspect, the present subject matter is directed to avision-based system for estimating and adjusting crop residue parametersas an implement is being towed across a field by a work vehicle. Thesystem may include an imaging device installed relative to one of thework vehicle or the implement such that the imaging device is configuredto capture images of the field. The system may also include a controllercommunicatively coupled to the imaging device, with the controllerincluding a processor and associated memory. The memory may storeinstructions that, when implemented by the processor, configure thecontroller to receive, from the imaging device, image data associatedwith an imaged portion of the field, analyze the image data using afirst residue-estimating technique to determine a first estimated valueof a crop residue parameter for the imaged portion of the field, andanalyze the image data using a second residue-estimating technique todetermine a second estimated value of the crop residue parameter for theimaged portion of the field, wherein the second residue-estimatingtechnique differs from the first residue-estimating technique. Moreover,when a differential exists between the first and second estimatedvalues, the controller may be configured to adjust at least one of thefirst estimated value or one or more additional estimated values of thecrop residue parameter determined using the first residue-estimatingtechnique based on at least one of the second estimated value or thedifferential between first and second estimated values.

These and other features, aspects and advantages of the presentinvention will become better understood with reference to the followingdescription and appended claims. The accompanying drawings, which areincorporated in and constitute a part of this specification, illustrateembodiments of the invention and, together with the description, serveto explain the principles of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

A full and enabling disclosure of the present invention, including thebest mode thereof, directed to one of ordinary skill in the art, is setforth in the specification, which makes reference to the appendedfigures, in which:

FIG. 1 illustrates a perspective view of one embodiment of a workvehicle towing an implement in accordance with aspects of the presentsubject matter;

FIG. 2 illustrates a perspective view of the implement shown in FIG. 1;

FIG. 3 illustrates a schematic view of one embodiment of a vision-basedsystem for acquiring crop residue data in accordance with aspects of thepresent subject matter;

FIG. 4 illustrates an example, simplified view of an image of a fieldacquired using an imaging device(s) of the disclosed system,particularly illustrating how the image may be analyzed using oneembodiment of a vision-based residue-estimating technique in accordancewith aspects of the present subject matter;

FIG. 5 illustrates an example, simplified view of a continuous imagedsection of a field acquired using an imaging device(s) of the disclosedsystem, particularly illustrating how the images associated with thecontinuous imaged section of the field may be analyzed using anotherembodiment of a vision-based residue-estimating technique in accordancewith aspects of the present subject matter;

FIG. 6 illustrates a flow diagram of one embodiment of a method forcalibrating crop residue data for a field acquired using a vision-basedsystem in accordance with aspects of the present subject matter.

DETAILED DESCRIPTION OF THE INVENTION

Reference now will be made in detail to embodiments of the invention,one or more examples of which are illustrated in the drawings. Eachexample is provided by way of explanation of the invention, notlimitation of the invention. In fact, it will be apparent to thoseskilled in the art that various modifications and variations can be madein the present invention without departing from the scope or spirit ofthe invention. For instance, features illustrated or described as partof one embodiment can be used with another embodiment to yield a stillfurther embodiment. Thus, it is intended that the present inventioncovers such modifications and variations as come within the scope of theappended claims and their equivalents.

In general, the present subject matter is directed to a vision-basedsystem for acquiring crop residue data associated with a field. Inaddition, the present subject matter is directed to methods forcalibrating crop residue acquired using a vision-based system.Specifically, in several embodiments, one or more imaging devices (e.g.,a camera(s)) may be provided in operative association with a workvehicle and/or an associated implement to capture images of a field asan operation (e.g., a tillage operation) is being performed within thefield. The images may then be automatically analyzed via an associatedcontroller using two different computer vision-based techniques toestimate a crop residue parameter for the imaged portion of the field(e.g., the percent crop residue coverage). For instance, a firstvision-based residue-estimating technique (e.g., a computer vision-basedblob analysis or other data extraction techniques) may be used todetermine a first estimated value for the crop residue parameterassociated with the imaged portion of the field while a secondvision-based residue-estimating technique (e.g., a computer vision-basedlinear transact method) may be used to determine a second estimatedvalue for the crop residue parameter associated with same imaged portionof the field. The first and second estimated values determined using thediffering residue-estimating techniques may then be compared todetermine whether a differential exists between the estimated values. Inthe event that the separate residue-estimating techniques providediffering values for the crop residue parameter, the estimated valuedetermined using one of the residue-estimating techniques may becalibrated or adjusted based on the estimated value determined using theother residue-estimating technique (or based on the differential betweenthe two estimated values) to improve the accuracy of the crop residuedata.

Referring now to drawings, FIGS. 1 and 2 illustrate perspective views ofone embodiment of a work vehicle 10 and an associated agriculturalimplement 12 in accordance with aspects of the present subject matter.Specifically, FIG. 1 illustrates a perspective view of the work vehicle10 towing the implement 12 (e.g., across a field). Additionally, FIG. 2illustrates a perspective view of the implement 12 shown in FIG. 1. Asshown in the illustrated embodiment, the work vehicle 10 is configuredas an agricultural tractor. However, in other embodiments, the workvehicle 10 may be configured as any other suitable agricultural vehicle.

As particularly shown in FIG. 1, the work vehicle 10 includes a pair offront track assemblies 14, a pair or rear track assemblies 16 and aframe or chassis 18 coupled to and supported by the track assemblies 14,16. An operator's cab 20 may be supported by a portion of the chassis 18and may house various input devices for permitting an operator tocontrol the operation of one or more components of the work vehicle 10and/or one or more components of the implement 12. Additionally, as isgenerally understood, the work vehicle 10 may include an engine 22 (FIG.3) and a transmission 24 (FIG. 3) mounted on the chassis 18. Thetransmission 24 may be operably coupled to the engine 22 and may providevariably adjusted gear ratios for transferring engine power to the trackassemblies 14, 16 via a drive axle assembly (not shown) (or via axles ifmultiple drive axles are employed).

Moreover, as shown in FIGS. 1 and 2, the implement 12 may generallyinclude a carriage frame assembly 30 configured to be towed by the workvehicle via a pull hitch or tow bar 32 in a travel direction of thevehicle (e.g., as indicated by arrow 34). As is generally understood,the carriage frame assembly 30 may be configured to support a pluralityof ground-engaging tools, such as a plurality of shanks, disk blades,leveling blades, basket assemblies, and/or the like. In severalembodiments, the various ground-engaging tools may be configured toperform a tillage operation across the field along which the implement12 is being towed.

As particularly shown in FIG. 2, the carriage frame assembly 30 mayinclude aft extending carrier frame members 36 coupled to the tow bar32. In addition, reinforcing gusset plates 38 may be used to strengthenthe connection between the tow bar 32 and the carrier frame members 36.In several embodiments, the carriage frame assembly 30 may generallyfunction to support a central frame 40, a forward frame 42 positionedforward of the central frame 40 in the direction of travel 34 of thework vehicle 10, and an aft frame 44 positioned aft of the central frame40 in the direction of travel 34 of the work vehicle 10. As shown inFIG. 2, in one embodiment, the central frame 40 may correspond to ashank frame configured to support a plurality of ground-engaging shanks46. In such an embodiment, the shanks 46 may be configured to till thesoil as the implement 12 is towed across the field. However, in otherembodiments, the central frame 40 may be configured to support any othersuitable ground-engaging tools.

Additionally, as shown in FIG. 2, in one embodiment, the forward frame42 may correspond to a disk frame configured to support various gangs orsets 48 of disk blades 50. In such an embodiment, each disk blade 50may, for example, include both a concave side (not shown) and a convexside (not shown). In addition, the various gangs 48 of disk blades 50may be oriented at an angle relative to the travel direction 34 of thework vehicle 10 to promote more effective tilling of the soil. However,in other embodiments, the forward frame 42 may be configured to supportany other suitable ground-engaging tools.

Moreover, similar to the central and forward frames 40, 42, the aftframe 44 may also be configured to support a plurality ofground-engaging tools. For instance, in the illustrated embodiment, theaft frame is configured to support a plurality of leveling blades 52 androlling (or crumbler) basket assemblies 54. However, in otherembodiments, any other suitable ground-engaging tools may be coupled toand supported by the aft frame 44, such as a plurality closing disks.

In addition, the implement 12 may also include any number of suitableactuators (e.g., hydraulic cylinders) for adjusting the relativepositioning, penetration depth, and/or down force associated with thevarious ground-engaging tools 46, 50, 52, 54. For instance, theimplement 12 may include one or more first actuators 56 coupled to thecentral frame 40 for raising or lowering the central frame 40 relativeto the ground, thereby allowing the penetration depth and/or the downpressure of the shanks 46 to be adjusted. Similarly, the implement 12may include one or more second actuators 58 coupled to the disk forwardframe 42 to adjust the penetration depth and/or the down pressure of thedisk blades 50. Moreover, the implement 12 may include one or more thirdactuators 60 coupled to the aft frame 44 to allow the aft frame 44 to bemoved relative to the central frame 40, thereby allowing the relevantoperating parameters of the ground-engaging tools 52, 54 supported bythe aft frame 44 (e.g., the down pressure and/or the penetration depth)to be adjusted.

It should be appreciated that the configuration of the work vehicle 10described above and shown in FIG. 1 is provided only to place thepresent subject matter in an exemplary field of use. Thus, it should beappreciated that the present subject matter may be readily adaptable toany manner of work vehicle configuration. For example, in an alternativeembodiment, a separate frame or chassis may be provided to which theengine, transmission, and drive axle assembly are coupled, aconfiguration common in smaller tractors. Still other configurations mayuse an articulated chassis to steer the work vehicle 10, or rely ontires/wheels in lieu of the track assemblies 14, 16.

It should also be appreciated that the configuration of the implement 12described above and shown in FIGS. 1 and 2 is only provided forexemplary purposes. Thus, it should be appreciated that the presentsubject matter may be readily adaptable to any manner of implementconfiguration. For example, as indicated above, each frame section ofthe implement 12 may be configured to support any suitable type ofground-engaging tools, such as by installing closing disks on the aftframe 44 of the implement 12.

Additionally, in accordance with aspects of the present subject matter,the work vehicle 10 and/or the implement 12 may include one or moreimaging devices coupled thereto and/or supported thereon for capturingimages or other image data associated with the field as an operation isbeing performed via the implement 12. Specifically, in severalembodiments, the imaging device(s) may be provided in operativeassociation with the work vehicle 10 and/or the implement 12 such thatthe imaging device(s) has a field of view directed towards a portion(s)of the field disposed in front of, behind, and/or along one or both ofthe sides of the work vehicle 10 and/or the implement 12 as theimplement 12 is being towed across the field. As such, the imagingdevice(s) may capture images from the tractor 10 and/or implement 12 ofone or more portion(s) of the field being passed by the tractor 10and/or implement 12.

In general, the imaging device(s) may correspond to any suitabledevice(s) configured to capture images or other image data of the fieldthat allow the field's soil to be distinguished from the crop residueremaining on top of the soil. For instance, in several embodiments, theimaging device(s) may correspond to any suitable camera(s), such assingle-spectrum camera or a multi-spectrum camera configured to captureimages in the visible light range and/or infrared spectral range.Additionally, in a particular embodiment, the camera(s) may correspondto a single lens camera configured to capture two-dimensional images ora stereo camera(s) having two or more lenses with a separate imagesensor for each lens to allow the camera(s) to capture stereographic orthree-dimensional images. Alternatively, the imaging device(s) maycorrespond to any other suitable image capture device(s) and/or visionsystem(s) that is capable of capturing “images” or other image-like datathat allow the crop residue existing on the soil to be distinguishedfrom the soil.

It should be appreciated that work vehicle 10 and/or implement 12 mayinclude any number of imaging device(s) 104 provided at any suitablelocation that allows images of the field to be captured as the vehicle10 and implement 12 traverse through the field. For instance, FIGS. 1and 2 illustrate examples of various locations for mounting one or moreimaging device(s) for capturing images of the field. Specifically, asshown in FIG. 1, in one embodiment, one or more imaging devices 104A maybe coupled to the front of the work vehicle 10 such that the imagingdevice(s) 104A has a field of view 106 that allows it to capture imagesof an adjacent area or portion of the field disposed in front of thework vehicle 10. For instance, the field of view 106 of the imagingdevice(s) 104A may be directed outwardly from the front of the workvehicle 10 along a plane or reference line that extends generallyparallel to the travel direction 34 of the work vehicle 10. In additionto such imaging device(s) 104A (or as an alternative thereto), one ormore imaging devices 104B may also be coupled to one of the sides of thework vehicle 10 such that the imaging device(s) 104B has a field of view106 that allows it to capture images of an adjacent area or portion ofthe field disposed along such side of the work vehicle 10. For instance,the field of view 106 of the imaging device(s) 104B may be directedoutwardly from the side of the work vehicle 10 along a plane orreference line that extends generally perpendicular to the traveldirection 34 of the work vehicle 10.

Similarly, as shown in FIG. 2, in one embodiment, one or more imagingdevices 104C may be coupled to the rear of the implement 12 such thatthe imaging device(s) 104C has a field of view 106 that allows it tocapture images of an adjacent area or portion of the field disposed aftof the implement. For instance, the field of view 106 of the imagingdevice(s) 104C may be directed outwardly from the rear of the implement12 along a plane or reference line that extends generally parallel tothe travel direction 34 of the work vehicle 10. In addition to suchimaging device(s) 104C (or as an alternative thereto), one or moreimaging devices 104D may also be coupled to one of the sides of theimplement 12 such that the imaging device(s) 104D has a field of view106 that allows it to capture images of an adjacent area or portion ofthe field disposed along such side of the implement 12. For instance,the field of view 106 of the imaging device 104D may be directedoutwardly from the side of the implement 12 along a plane or referenceline that extends generally perpendicular to the travel direction 34 ofthe work vehicle 10.

It should be appreciated that, in alternative embodiments, the imagingdevice(s) 104 may be installed at any other suitable location thatallows the device(s) to capture images of an adjacent portion of thefield, such as by installing an imaging device(s) at or adjacent to theaft end of the work vehicle 10 and/or at or adjacent to the forward endof the implement 10. It should also be appreciated that, in severalembodiments, the imaging devices 104 may be specifically installed atlocations on the work vehicle 10 and/or the implement 12 to allow imagesto be captured of the field both before and after the performance of afield operation by the implement 12. For instance, by installing theimaging device 104A at the forward end of the work vehicle 10 and theimaging device 104C at the aft end of the implement 12, the forwardimaging device 104A may capture images of the field prior to performanceof the field operation while the aft imaging device 104C may captureimages of the same portions of the field following the performance ofthe field operation.

Referring now to FIG. 3, a schematic view of one embodiment of avision-based system 100 for estimating crop residue parameters isillustrated in accordance with aspects of the present subject matter. Ingeneral, the system 100 will be described herein with reference to thework vehicle 10 and the implement 12 described above with reference toFIGS. 1 and 2. However, it should be appreciated that the disclosedsystem 100 may generally be utilized with work vehicles having anysuitable vehicle configuration and/or implements have any suitableimplement configuration.

In several embodiments, the system 100 may include a controller 102 andvarious other components configured to be communicatively coupled toand/or controlled by the controller 102, such as one or more imagingdevices 104 and/or various components of the work vehicle 10 and/or theimplement 12. As will be described in greater detail below, thecontroller 102 may be configured to receive images or other image datafrom the imaging device(s) 104 that depict portions of the field as anoperation (e.g., a tillage operation) is being performed within thefield. Based on an analysis of the image data received from the imagingdevice(s) 104, the controller 102 may be configured to estimate a firstvalue for a crop residue parameter associated with the field (e.g., apercent crop residue coverage) using a first residue-estimatingtechnique. Thereafter, the controller 102 may be configured to analyzethe same or similar images or other image data to estimate a secondvalue for the crop residue parameter using a second residue-estimatingtechnique that differs from the first residue-estimating technique.Based on a comparison between the estimated values for the crop residueparameter determined using the two differing techniques, the controllermay, if necessary or desired, calibrate the crop residue date beinggenerated using one of the residue-estimating technique, such as byadjusting the first estimated value for the crop residue parameterdetermined using the first residue-estimating technique based on thesecond estimated value determined using the second residue-estimatingtechnique.

In general, the controller 102 may correspond to any suitableprocessor-based device(s), such as a computing device or any combinationof computing devices. Thus, as shown in FIG. 3, the controller 102 maygenerally include one or more processor(s) 110 and associated memorydevices 112 configured to perform a variety of computer-implementedfunctions (e.g., performing the methods, steps, algorithms, calculationsand the like disclosed herein). As used herein, the term “processor”refers not only to integrated circuits referred to in the art as beingincluded in a computer, but also refers to a controller, amicrocontroller, a microcomputer, a programmable logic controller (PLC),an application specific integrated circuit, and other programmablecircuits. Additionally, the memory 112 may generally comprise memoryelement(s) including, but not limited to, computer readable medium(e.g., random access memory (RAM)), computer readable non-volatilemedium (e.g., a flash memory), a floppy disk, a compact disc-read onlymemory (CD-ROM), a magneto-optical disk (MOD), a digital versatile disc(DVD) and/or other suitable memory elements. Such memory 112 maygenerally be configured to store information accessible to theprocessor(s) 110, including data 114 that can be retrieved, manipulated,created and/or stored by the processor(s) 110 and instructions 116 thatcan be executed by the processor(s) 110.

In several embodiments, the data 114 may be stored in one or moredatabases. For example, the memory 112 may include an image database 118for storing image data received from the imaging device(s) 104. Forexample, the imaging device(s) 104 may be configured to continuously orperiodically capture images of adjacent portion(s) of the field as anoperation is being performed with the field. In such an embodiment, theimages transmitted to the controller 102 from the imaging device(s) 104may be stored within the image database 118 for subsequent processingand/or analysis. It should be appreciated that, as used herein, the termimage data may include any suitable type of data received from theimaging device(s) 104 that allows for the crop residue coverage of afield to be analyzed, including photographs and other image-related data(e.g., scan data and/or the like).

Additionally, as shown in FIG. 3, the memory 12 may include a cropresidue database 120 for storing information related to crop residueparameters for the field being processed. For example, as indicatedabove, based on the image data received from the imaging device(s) 104,the controller 102 may be configured to estimate or calculate one ormore values for one or more crop residue parameters associated with thefield, such as a value(s) for the percent crop residue coverage for animaged portion(s) of the field (and/or a value(s) for the averagepercent crop residue coverage for the field). The crop residueparameter(s) estimated or calculated by the controller 102 may then bestored within the crop residue database 120 for subsequent processingand/or analysis.

Moreover, in several embodiments, the memory 12 may also include alocation database 122 storing location information about the workvehicle/implement 10, 12 and/or information about the field beingprocessed (e.g., a field map). Specifically, as shown in FIG. 3, thecontroller 102 may be communicatively coupled to a positioning device(s)124 installed on or within the work vehicle 10 and/or on or within theimplement 12. For example, in one embodiment, the positioning device(s)124 may be configured to determine the exact location of the workvehicle 10 and/or the implement 12 using a satellite navigation positionsystem (e.g. a GPS system, a Galileo positioning system, the GlobalNavigation satellite system (GLONASS), the BeiDou Satellite Navigationand Positioning system, and/or the like). In such an embodiment, thelocation determined by the positioning device(s) 124 may be transmittedto the controller 102 (e.g., in the form coordinates) and subsequentlystored within the location database 122 for subsequent processing and/oranalysis.

Additionally, in several embodiments, the location data stored withinthe location database 122 may also be correlated to the image datastored within the image database 118. For instance, in one embodiment,the location coordinates derived from the positioning device(s) 124 andthe image(s) captured by the imaging device(s) 104 may both betime-stamped. In such an embodiment, the time-stamped data may alloweach image captured by the imaging device(s) 104 to be matched orcorrelated to a corresponding set of location coordinates received fromthe positioning device(s) 124, thereby allowing the precise location ofthe portion of the field depicted within a given image to be known (orat least capable of calculation) by the controller 102.

Moreover, by matching each image to a corresponding set of locationcoordinates, the controller 102 may also be configured to generate orupdate a corresponding field map associated with the field beingprocessed. For example, in instances in which the controller 102 alreadyincludes a field map stored within its memory 112 that includes locationcoordinates associated with various points across the field, each imagecaptured by the imaging device(s) 104 may be mapped or correlated to agiven location within the field map. Alternatively, based on thelocation data and the associated image data, the controller 102 may beconfigured to generate a field map for the field that includes thegeo-located images associated therewith.

Referring still to FIG. 3, in several embodiments, the instructions 116stored within the memory 112 of the controller 102 may be executed bythe processor(s) 110 to implement an image analysis module 126. Ingeneral, the image analysis module 126 may be configured to analyze theimages received by the imaging device(s) 104 using one or moreresidue-estimating techniques to allow the controller 102 to estimateone or more crop residue parameters associated with the field currentlybeing processed. For instance, in several embodiments, the imageanalysis module 126 may be configured to implement two differentresidue-estimating techniques (e.g., first and second residue-estimatingtechniques), with each residue-estimating technique being based on adifferent computer-vision algorithm or any other suitableimage-processing technique that allows the controller 102 to identifycrop residue remaining on top of the soil. By identifying all or aportion of the crop residue contained within each image (or within asubset of the images) using the two different residue-estimatingtechniques, the controller 102 may then determine two values for thecrop residue parameter(s) associated with a given imaged portion of thefield. Such values may then be stored within the crop residue database120.

It should be appreciated that, in general, the residue-estimatingtechniques used by the image analysis module 126 to estimate the cropresidue parameter(s) may correspond to any suitable computer-visionalgorithms or image-processing techniques that allow the controller 102to identify crop residue remaining on top of the soil. For instance, aswill be described below with reference to FIGS. 4 and 5, in oneembodiment, the image analysis module may be configured to utilize botha computer vision-based blob analysis and a computer vision-based lineartransact method to estimate values for the crop residue parameter(s).The estimated values determined using each of such residue-estimatingtechniques may then be stored within the crop residue database 120 forsubsequent analysis and/or processing. However, in other embodiments,the image analysis module 126 may be configured to implement any othersuitable vision-based residue-estimating techniques to estimate the cropresidue parameter(s).

Moreover, as shown in FIG. 3, the instructions 116 stored within thememory 112 of the controller 102 may also be executed by theprocessor(s) 110 to implement a calibration module 128. In general, thecalibration module 128 may be configured to calibrate the crop residuedata generated by the image analysis module 126 based on the estimatedvalues determined using the differing residue-estimating techniques.Specifically, in several embodiments, the calibration module 128 may beconfigured to compare the estimated value(s) of the crop residueparameter(s) determined using the first residue-estimating technique tothe corresponding estimate value(s) of the crop residue parameter(s)determined using the second residue-estimating technique. In suchembodiments, when a differential exists between the estimate value(s)determined using the first residue-estimating technique and thecorresponding estimate value(s) determined using the secondresidue-estimating technique, the calibration module 128 may beconfigured to calibrate or adjust the estimated value(s) determinedusing one of the residue-estimating techniques based on the estimatedvalue(s) determined using the other residue-estimating technique.

For instance, in one embodiment, the estimated value(s) determined usingthe second residue-estimating technique may be used to calibrate oradjust the estimate value(s) determined using the firstresidue-estimating technique. As an example, assuming thatresidue-estimating techniques are being used to determine estimatedvalues of the percent crop residue coverage within the field, the imageanalysis module 126 may analyze one or more images of an imaged portionof the field and determine a first estimated value of 45% crop residuecoverage using the first residue-estimating technique and a secondestimated value of 50% crop residue coverage using the secondresidue-estimating technique. The calibration module 128 may thencompare the first and estimated values and determine that a +5%differential exists between the estimated values. The calibration module128 may then, in one embodiment, adjust the first estimated value and/orany future/past estimated values determined using the firstresidue-estimating technique based on the second estimated value and/orthe differential determined between the first and second estimatedvalues. For instance, the calibration module 128 may be configured toincrease the first estimated value and/or any future/past estimatedvalues determined using the first residue-estimating technique by 5% toensure that the crop residue data generated using the firstresidue-estimating technique is consistent with the crop residue datagenerated using the second residue-estimating technique.

It should be appreciated that, in addition to analyzing the estimatedvalues determined for a singled imaged portion of the field or as analternative thereto, the calibration module 128 may be configured toanalyze the estimated values determined for various different imagedportions of the field. In such an embodiment, the calibration module 128may be configured to compare the estimated values determined using thefirst and second residue-estimating techniques for each imaged portionof the field to determine an average differential existing between thefirst and second estimated values. The calibration module 128 may thenadjust the first estimated value and/or any future/past estimated valuesdetermined using the first residue-estimating technique based on theaverage differential determined across the various imaged portions ofthe field.

Additionally, it should be appreciated that, although the presentsubject matter is generally described herein as using the secondestimated value(s) determined via the second residue-estimatingtechnique to calibrate or adjust the first estimate value(s) determinedvia the first residue-estimating technique, the configuration may bereversed, with the first estimated value(s) being used to calibrate oradjust the second estimated value(s). In general, the residue-estimatingtechnique used as the calibration source may be selected based on anynumber of factors, including accuracy considerations, computerprocessing requirements, standards or regulations set for crop residuedata and/or the like.

Referring still to FIG. 3, the instructions 116 stored within the memory112 of the controller 102 may also be executed by the processor(s) 110to implement a control module 129. In general, the control module 129may be configured to adjust the operation of the work vehicle 10 and/orthe implement 12 by controlling one or more components of theimplement/vehicle 12, 10. Specifically, in several embodiments, when theestimated crop residue parameter determined by the controller 102differs from a given target set for such parameter, the control module129 may be configured to fine-tune the operation of the work vehicle 10and/or the implement 12 in a manner designed to adjust the amount ofcrop residue remaining in the field. For instance, when it is desired tohave a percent crop residue coverage of 30%, the control module 129 maybe configured to adjust the operation of the work vehicle and/or theimplement 12 so as to increase or decrease the amount of crop residueremaining in the field when the estimated percent crop residue coveragefor a given imaged portion of the field (or an average estimated percentcrop residue coverage across multiple imaged portions of the field)differs from the target percentage.

It should be appreciated that the controller 102 may be configured toimplement various different control actions to adjust the operation ofthe work vehicle 10 and/or the implement 12 in a manner that increasesor decreases the amount of crop residue remaining in the field. In oneembodiment, the controller 102 may be configured to increase or decreasethe operational or ground speed of the implement 12 to affect anincrease or decrease in the crop residue coverage. For instance, asshown in FIG. 3, the controller 102 may be communicatively coupled toboth the engine 22 and the transmission 24 of the work vehicle 10. Insuch an embodiment, the controller 102 may be configured to adjust theoperation of the engine 22 and/or the transmission 24 in a manner thatincreases or decreases the ground speed of the work vehicle 10 and,thus, the ground speed of the implement 12, such as by transmittingsuitable control signals for controlling an engine or speed governor(not shown) associated with the engine 22 and/or transmitting suitablecontrol signals for controlling the engagement/disengagement of one ormore clutches (not shown) provided in operative association with thetransmission 24.

In addition to the adjusting the ground speed of the vehicle/implement10, 12 (or as an alternative thereto), the controller 102 may also beconfigured to adjust an operating parameter associated with theground-engaging tools of the implement 12. For instance, as shown inFIG. 3, the controller 102 may be communicatively coupled to one or morevalves 130 configured to regulate the supply of fluid (e.g., hydraulicfluid or air) to one or more corresponding actuators 56, 58, 60 of theimplement 12. In such an embodiment, by regulating the supply of fluidto the actuator(s) 56, 58, 60, the controller 102 may automaticallyadjust the penetration depth, the down force, and/or any other suitableoperating parameter associated with the ground-engaging tools of theimplement 12.

Moreover, as shown in FIG. 3, the controller 102 may also include acommunications interface 132 to provide a means for the controller 102to communicate with any of the various other system components describedherein. For instance, one or more communicative links or interfaces 134(e.g., one or more data buses) may be provided between thecommunications interface 132 and the imaging device(s) 104 to allowimages transmitted from the imaging device(s) 104 to be received by thecontroller 102. Similarly, one or more communicative links or interfaces136 (e.g., one or more data buses) may be provided between thecommunications interface 132 and the positioning device(s) 124 to allowthe location information generated by the positioning device(s) 124 tobe received by the controller 102. Additionally, as shown in FIG. 3, oneor more communicative links or interfaces 138 (e.g., one or more databuses) may be provided between the communications interface 132 and theengine 22, the transmission 24, the control valves 130, and/or the liketo allow the controller 102 to control the operation of such systemcomponents.

Referring now to FIG. 4, an example, simplified image of a portion of afield that may be provided by one of the imaging device(s) 104 of thedisclosed system 100 is illustrated in accordance with aspects of thepresent subject matter, particularly illustrating the field includingcrop residue 160 (indicated by cross-hatching) positioned on the top ofthe soil 162. As indicated above, the image analysis module 126 of thecontroller 102 may generally be configured to utilize any suitablecomputer-vision algorithms or image-processing techniques that allow thecontroller 102 to identify crop residue 160 remaining on top of the soil162. For instance, in one embodiment, the vision-based technique used bythe image analysis module 126 may rely upon the identification of one ormore image characteristics captured by the imaging device(s) 104 todistinguish the crop residue 160 from the soil 162 contained within eachimage. For instance, when the imaging device(s) 104 corresponds to acamera capable of capturing the distinction between the reflectivecharacteristics of the soil 162 and the crop residue 160, the controller102 may be configured to implement a computer-vision algorithm thatidentifies the differences in the reflectivity or spectral absorptionbetween the soil 162 and the crop residue 160 contained within eachimage being analyzed. Alternatively, the controller 102 may beconfigured to utilize an edge-finding algorithm to identify ordistinguish the crop residue 160 from the soil 162 contained within eachimage.

Additionally, upon distinguishing the crop residue 160 from the soil162, the controller 102 may be configured to utilize any suitabletechnique or methodology for calculating the percent crop residuecoverage for the portion of the field contained within each image. Forinstance, as indicated above, the controller 102 may, in one embodiment,utilize a “blob analysis” in which the crop residue identified withineach image via the associated computer-vision technique is representedas a “blob” or plurality of“blobs” encompassing a given area within theimage. Specifically, as shown in FIG. 4, the crop residue 160 depictedwithin the image is represented as cross-hatched blobs overlaying thesoil 162. In such an embodiment, the image analysis module 126 may beconfigured to calculate the percent crop residue coverage for the imagedportion of the field using the following equation (Equation 1):

$\begin{matrix}{{{Percent}\mspace{14mu} {Crop}\mspace{14mu} {Residue}} = {\left( {1 - \frac{\left( {{{total}\mspace{14mu} {image}\mspace{14mu} {area}} - {{blob}\mspace{14mu} {area}}} \right)}{{total}\mspace{14mu} {image}\mspace{14mu} {area}}} \right)*100}} & (1)\end{matrix}$

wherein, the total image area corresponds to the total area definedwithin the image (e.g., as a function of the total number of pixels ofthe image) and the blob area corresponds to the total area representedby crop residue 160 within the image (e.g., as a function of the totalnumber of pixels representing the identified crop residue).

Referring now to FIG. 5, an example, simplified view of a continuoussection 170 of an imaged portion of a field is illustrated in accordancewith aspects of the present subject matter. Specifically, FIG. 5illustrates a plurality of images captured by one or more of the imagingdevice(s) 104 of the disclosed system 100 that collectively depict acontinuous section 170 of the field. For instance, the field of view 106of the imaging device(s) 104 may allow the imaging device(s) 104 tocapture an image of the field that spans a given field distance. In suchan embodiment, to analyze a continuous section 170 of an imaged portionof the field that extends across a predetermined field length 172 thatis greater than the field distance captured within each image, multipleimages may be stitched together or otherwise analyzed in combination.For instance, in the example view shown in FIG. 5, a plurality of imagescaptured by one of the imaging device(s) 104 have been stitched together(e.g., the separate images being indicated by the dashed horizontallines) to provide a view of a continuous section 170 of the field thatspans across a predetermined field length 172.

It should be appreciated that the controller 102 (e.g., the imageanalysis module 126) may be configured to identify which images can beused to collectively depict a continuous section of the field using anysuitable methodology or technique. For instance, as indicated above, theimages provided by the imaging device(s) 104 may be time-stamped. Insuch an embodiment, by knowing the ground speed of the workvehicle/implement 10, 12 and the field of view 106 of the imagingdevice(s) 104 relative to the field, the controller 102 may beconfigured to stitch together or otherwise access the images captured bythe imaging device(s) 104 that collectively depict a continuous fieldsection 170 spanning across the predetermined field length 172.Alternatively, the controller 102 may be configured to utilize anysuitable image-processing algorithm that allows the controller 102 toidentify the images (or portions of images) that collectively depict acontinuous section of the field.

By capturing images that collectively depict a continuous section 170 ofthe field, the image analysis module 126 of the controller 102 may, inseveral embodiments, be configured to implement a computer vision-basedline transact method to estimate the percent crop residue coverage forthe imaged portion of the field. Specifically, in several embodiments,the image analysis module 126 may access the images collectivelydepicting the continuous imaged section 170 of the field and apply aknown scale 174 to such continuous imaged section 170 of the field suchthat a plurality of reference points 176 are defined along thecontinuous imaged field section 170 that are spaced apart evenly acrossthe predetermined field length 172. Thereafter, the images may beanalyzed to identify the number or percentage of reference points 176that are aligned with or intersect crop residue within the continuousimaged section 170 of the field. Such identified number or percentage ofthe reference points 176 may then correspond to or may be used tocalculate the percent crop residue coverage within the continuous imagedsection 170 of the field. For example, in one embodiment, the percentcrop residue coverage for the continuous imaged section 170 of the fieldmay be calculated using the following equation (Equation 2):

$\begin{matrix}{{{Percent}\mspace{14mu} {Crop}\mspace{14mu} {Residue}} = {\left( {1 - \frac{\left( {{identified}\mspace{14mu} {reference}\mspace{14mu} {points}} \right)}{{total}\mspace{14mu} {reference}\mspace{14mu} {points}}} \right)*100}} & (2)\end{matrix}$

wherein, the “identified reference points” correspond to the totalnumber of reference points 176 identified by the image analysis module126 that are aligned with or intersect crop residue with the analyzedimages and the “total reference points” correspond to the total numberof reference points 176 defined across the predetermined field length172 via the applied scale 174.

In several embodiments, the scale 174 applied to the continuous imagedsection 170 of the field may divide the predetermined field length 172into one hundred distinct field sections such that one hundred referencepoints 176 are evenly spaced apart along the predetermined field length170. In such an embodiment, it may be desirable for the continuousimaged section 170 of the field to correspond to a continuous fieldsection spanning one hundred feet (i.e., such that the predeterminedfield length 172 is equal to one hundred feet). As a result, the imposedscale 174 may divide the predetermined field length 172 into one hundredone-foot sections, with a reference point 176 being defined at each footmark along the predetermined field length 172. However, in otherembodiments, the predetermined field length 172 may correspond to anyother suitable field length, such as a fifty foot field section, atwenty-five foot field section or any other suitable field length.Similarly, any other suitable scale 174 may be applied to the continuousimaged section 170 of the field to allow any suitable number of evenlyspaced reference points 176 to be defined across the predetermined fieldlength 172. For instance, in alternative embodiments, a fifty-pointscale or a twenty-five-point scale may be applied such that fifty ortwenty-five evenly spaced reference points 176, respectively, aredefined across the predetermined field length 172.

It should be appreciated that, in several embodiments, the imageanalysis module 126 may only be configured to identify the referencepoints 176 within the images that are aligned with or intersect cropresidue that exceeds a given residue size threshold for purposes ofcalculating the percent crop residue coverage for the continuous imagedsection 170 of the field. Specifically, in several embodiments, the sizethreshold for the crop residue may be selected based on the minimumresidue size capable of intercepting rain drops. For instance, in oneembodiment, the residue size threshold may correspond to a residuediameter of one-eighth of an inch (⅛″). In such an embodiment, if thecrop residue aligned with or intersecting one of the reference points176 is determined to have a cross-wise dimension within the image thatexceeds ⅛″ (e.g., via a suitable image analysis technique), suchreference point 176 may be counted for purposes of calculating thepercent crop residue coverage for the continuous imaged section 170 ofthe field. However, if the crop residue aligned with or intersecting oneof the reference points 176 is determined to have a cross-wise dimensionwithin the image that is less than ⅛″, such reference point 176 may notbe counted for purposes of calculating the percent crop residuecoverage.

It should also be appreciated that, in several embodiments, the imageanalysis module 126 may be configured to perform the above-referencedanalysis for multiple imaged sections of the field. For example, theimage analysis module 126 may access images captured by the imagingdevice(s) 104 that collectively depict several different continuousimaged sections of the field, with each continuous imaged field sectionspanning a predetermined field length. Thereafter, for each continuousimaged section of the field, the image analysis module 126 may apply aknown scale to such continuous imaged field section such that aplurality of reference points are defined along the continuous imagedfield section that are spaced apart evenly across the predeterminedfield length. The images associated with each continuous imaged sectionof the field may then be analyzed to identify the number or percentageof reference points that are aligned with or intersect crop residuewithin such continuous imaged section of the field, thereby allowing avalue for the percent crop residue coverage to be determined for eachcontinuous imaged field section. In such an embodiment, the imageanalysis module 126 may then calculate an average percent crop residuecoverage based on the residue coverage values calculated for the variouscontinuous imaged field sections. In doing so, it may be desirable forthe average percent crop residue coverage to be calculated based on theresidue coverage values determined for at least five continuous imagedfield sections, thereby allowing a desirable confidence level to beobtained for the calculated average.

Referring now to FIG. 6, a flow diagram of one embodiment of a method200 for calibrating crop residue data acquired using a vision-basedsystem is illustrated in accordance with aspects of the present subjectmatter. In general, the method 200 will be described herein withreference to the work vehicle 10 and the implement 12 shown in FIGS. 1and 2, as well as the various system components shown in FIG. 3.However, it should be appreciated that the disclosed method 200 may beimplemented with work vehicles and/or implements having any othersuitable configurations and/or within systems having any other suitablesystem configuration. In addition, although FIG. 6 depicts stepsperformed in a particular order for purposes of illustration anddiscussion, the methods discussed herein are not limited to anyparticular order or arrangement. One skilled in the art, using thedisclosures provided herein, will appreciate that various steps of themethods disclosed herein can be omitted, rearranged, combined, and/oradapted in various ways without deviating from the scope of the presentdisclosure.

As shown in FIG. 6, at (202), the method 200 may include controlling theoperation of at least one of an implement or a work vehicle as theimplement is being towed by the work vehicle across a field.Specifically, as indicated above, the controller 102 of the disclosedsystem 100 may be configured to control the operation of the workvehicle 10 and/or the implement 12, such as by controlling one or morecomponents of the work vehicle 10 and/or the implement 12 to allow anoperation to be performed within the field (e.g., a tillage operation).

Additionally, at (204), the method 200 may include receiving image dataassociated with an imaged portion of the field. Specifically, asindicated above, the controller 102 may be coupled to one or moreimaging devices 104 configured to capture images of various portions ofthe field.

Moreover, at (206), the method 200 may include analyzing the image datausing a first residue-estimating technique to determine a firstestimated value of a crop residue parameter for the imaged portion ofthe field. For instance, as indicated above, the image analysis module126 of the controller 102 may be configured to implement a vision-basedresidue-estimating technique to estimate a crop residue parameter forthe imaged portion of the field, such as by estimating the percent cropresidue coverage for the imaged portion of the field using a computervision-based blob analysis or using a computer vision-based linetransact method.

Referring still to FIG. 6, at (208), the method 200 may includeanalyzing the image data using a second residue-estimating technique todetermine a second estimated value of the crop residue parameter for theimaged portion of the field. Specifically, as indicated above, the imageanalysis module 126 of the controller 102 may, in accordance withaspects of the present subject matter, be configured to implement twodifferent vision-based residue-estimating techniques for estimating agiven crop residue parameter for the imaged portion of the field. Forinstance, in an embodiment in which the first residue-estimatingtechnique corresponds to a computer vision-based blob analysis, thesecond residue estimating technique may, for example, correspond to acomputer vision-based line transact method or vice versa. As such, thecontroller 102 may determine two separate estimated values for the cropreside parameter using the two different residue-estimating techniques.

Additionally, at (210), the method 200 may include adjusting at leastone of the first estimated value or one or more additional estimatedvalues of the crop residue parameter obtained using the firstresidue-estimating technique based on at least one of the secondestimated value or the differential between first and second estimatedvalues. Specifically, as indicated above, when a differential existsbetween the first and second estimated values, the controller 102 may beconfigured to adjust the first estimated value determined using thefirst residue-estimated technique based on the second estimated valuedetermined using the second residue-estimated technique and/or based onthe differential existing between the first and second estimated values.For example, assuming that a percent crop residue coverage of 40% isdetermined using the first residue-estimating technique and a percentcrop residue coverage of 32% is determined using the secondresidue-estimating technique, the controller 102 may, in one embodiment,the adjust the estimated percent crop residue coverage associated withthe first residue-estimating technique to match the percent crop residuecoverage associated with the second residue-estimating technique (e.g.,by reducing the percent crop residue coverage from 40% to 32%). Inaddition, the controller 102 may also utilize the differential definedbetween the first and second estimated values to adjust any past orfuture estimated values determined using the first residue-estimatingtechnique, such as by applying a −8% modifier to each estimated valuedetermined using the first residue-estimating technique.

It should be appreciated that, although not shown, the method 200 mayalso include any additional steps or method elements consistent with thedisclosure provided herein. For example, the method 200 may also includeactively adjusting the operation of the implement 12 and/or the workvehicle 10 when the adjusted value for the first estimated value and/orthe adjusted value(s) for the one or more additional estimated valuesdetermined using the first residue-estimating technique differs from atarget value set for crop residue parameter. Specifically, as indicatedabove, when the estimated crop residue parameter differs from a targetvalue set for such parameter, the controller 102 may be configured toactively adjust the operation of the work vehicle 10 and/or theimplement 12 in a manner that increases or decreases the amount of cropresidue remaining within the field following the operation beingperformed (e.g., a tillage operation), such as by adjusting the groundspeed at which the implement 12 is being towed and/or by adjusting oneor more operating parameters associated with the ground-engagingelements of the implement 12.

This written description uses examples to disclose the invention,including the best mode, and also to enable any person skilled in theart to practice the invention, including making and using any devices orsystems and performing any incorporated methods. The patentable scope ofthe invention is defined by the claims, and may include other examplesthat occur to those skilled in the art. Such other examples are intendedto be within the scope of the claims if they include structural elementsthat do not differ from the literal language of the claims, or if theyinclude equivalent structural elements with insubstantial differencesfrom the literal languages of the claims.

What is claimed is:
 1. A method for calibrating crop residue data for afield acquired using a vision-based system, the method comprising:controlling, with a computing device, an operation of at least one of animplement or a work vehicle as the implement is being towed by the workvehicle across the field; receiving, with the computing device, imagedata associated with an imaged portion of the field; analyzing, with thecomputing device, the image data using a first residue-estimatingtechnique to determine a first estimated value of a crop residueparameter for the imaged portion of the field; analyzing, with thecomputing device, the image data using a second residue-estimatingtechnique to determine a second estimated value of the crop residueparameter for the imaged portion of the field, the secondresidue-estimating technique differing from the first residue-estimatingtechnique; and when a differential exists between the first and secondestimated values, adjusting, with the computing device, at least one ofthe first estimated value or one or more additional estimated values ofthe crop residue parameter determined using the first residue-estimatingtechnique based on at least one of the second estimated value or thedifferential between first and second estimated values.
 2. The method ofclaim 1, wherein receiving image data associated with the imaged portionof the field comprises receiving the image data from one or more imagingdevices provided in operative association with at least one of the workvehicle or the implement.
 3. The method of claim 1, wherein the cropresidue parameter corresponds to a percent crop residue coverageassociated with the imaged portion of the field.
 4. The method of claim1, wherein analyzing the image data using the first residue-estimatingtechnique comprises analyzing the image data using a computervision-based image processing technique.
 5. The method of claim 4,wherein the computer vision-based image processing technique correspondsto a vision-based blob analysis of the image data to determine the firstestimated value of the crop residue parameter for the imaged portion ofthe field.
 6. The method of claim 1, wherein analyzing the image datausing the second residue-estimating technique comprises analyzing theimage data using a computer vision-based line transact method.
 7. Themethod of claim 6, wherein analyzing the image data using the computervision-based line transact method comprises: accessing a plurality ofimages of the image data that collectively depict a continuous imagedsection of the field, the continuous imaged section extending across apredetermined length; applying a known scale to the continuous imagedsection of the field such that a plurality of reference points areassociated with the continuous imaged section; and determining apercentage of the plurality of reference points that are aligned with orintersect crop residue within the plurality of images.
 8. The method ofclaim 7, further comprises determining the second estimated value of thecrop residue parameter based at least in part on the percentage of theplurality of reference points that are aligned with or intersect cropresidue within the plurality of images.
 9. The method of claim 7,wherein determining the percentage of the plurality of reference pointsthat are aligned with or intersect crop residue within the plurality ofimages comprises determining the percentage of the plurality ofreference points that are aligned with or intersect crop residue thatexceeds a given size threshold.
 10. The method of claim 7, whereinapplying the known scale to the continuous imaged section of the fieldcomprises applying the known scale such that the plurality of referencepoints are spaced apart evenly across the predetermined length.
 11. Themethod of claim 7, further comprising: accessing a second plurality ofimages of the image data that collectively depict one or more additionalcontinuous imaged sections of the field, each of the one or moreadditional continuous imaged sections of the field extending across thepredetermined length; applying the known scale to the one moreadditional continuous imaged sections of the field such that a pluralityof reference points are associated with each of the one or moreadditional continuous imaged sections of the field; determining apercentage of the plurality of reference points that are aligned with orintersect crop residue within the second plurality of images for each ofthe one or more additional continuous imaged sections of the field; anddetermining the second estimated value of the crop residue parameterbased on an average of the determined percentages associated with thecontinuous image section of the field and the one or more additionalcontinuous imaged sections of the field.
 12. The method of claim 1,further comprising actively adjusting the operation of at least one ofthe implement or the work vehicle when the adjusted value for the atleast one of the first estimated value or the one or more additionalestimated values differs from a target value set for the crop residueparameter.
 13. A vision-based system for estimating and adjusting cropresidue parameters as an implement is being towed across a field by awork vehicle, the system comprising: an imaging device installedrelative to one of the work vehicle or the implement such that theimaging device is configured to capture images of the field; acontroller communicatively coupled to the imaging device, the controllerincluding a processor and associated memory, the memory storinginstructions that, when implemented by the processor, configure thecontroller to: receive, from the imaging device, image data associatedwith an imaged portion of the field; analyze the image data using afirst residue-estimating technique to determine a first estimated valueof a crop residue parameter for the imaged portion of the field; analyzethe image data using a second residue-estimating technique to determinea second estimated value of the crop residue parameter for the imagedportion of the field, the second residue-estimating technique differingfrom the first residue-estimating technique; and when a differentialexists between the first and second estimated values, adjust at leastone of the first estimated value or one or more additional estimatedvalues of the crop residue parameter determined using the firstresidue-estimating technique based on at least one of the secondestimated value or the differential between first and second estimatedvalues.
 14. The system of claim 13, wherein the imaging device comprisesa camera.
 15. The system of claim 13, wherein the imaging device isinstalled relative to one of the work vehicle or the implement such thata field of view of the imaging device is directed either parallel orperpendicular to a travel direction of the work vehicle.
 16. The systemof claim 13, wherein the crop residue parameter corresponds to a percentcrop residue coverage associated with the imaged portion of the field.17. The system of claim 13, wherein the second residue-estimatingtechnique corresponds to a computer vision-based line transact method.18. The system of claim 18, wherein, when analyzing the image data usingthe computer vision-based line transact method, the controller isconfigured to: access a plurality of images of the image data thatcollectively depict a continuous imaged section of the field, thecontinuous imaged section extending across a predetermined length; applya known scale to the continuous imaged section of the field such that aplurality of reference points are associated with the continuous imagedsection; and determine a percentage of the plurality of reference pointsthat are aligned with or intersect crop residue within the plurality ofimages.
 19. The system of claim 18, wherein the controller is configuredto determine the second estimated value of the crop residue parameterbased at least in part on the percentage of the plurality of referencepoints that are aligned with or intersect crop residue within theplurality of images.
 20. The system of claim 13, wherein the controlleris further configured to actively adjust the operation of at least oneof the implement or the work vehicle when the adjusted value for the atleast one of the first estimated value or the one or more additionalestimated values differs from a target value set for the crop residueparameter.